Figure - available from: Quality & Quantity
This content is subject to copyright. Terms and conditions apply.
Source publication
This study investigates the non-linear cointegrating relationship between wholesale electricity prices (WEP) and electricity generation from conventional sources (EGCS), using data for India. The conventional sources considered in the analysis are thermal, nuclear, and hydro. The dataset is a monthly time series covering the period from April 2012...
Similar publications
This paper presents the energy security, energy poverty, and mediating role of environmental tax policy. The environmental tax policy affects energy consumption and energy poverty. The research applied multiple, comprehensive, and relevant sets of indicators to measure energy security, energy poverty, and environmental consideration of energy pover...
Citations
Diversification of energy mix is related to the heterogeneity of contributions of energy sources in the energy consumption basket of nations. Its persistent degree reveals the efficiency of energy-related policies or shocks to diversify the contributions of energy sources in the energy mix. For the first time, the current study measures the diversification level of energy mix of the USA and its 51 states and examines its stochastic behavior to analyze its degree of persistence. To this end, we calculated the diversification of energy mix using Herfindahl–Hirschman index over the period 1960−2020. Then, we applied two novel versions of LM unit root tests that can incorporate sharp or smooth breaks and common factors (to control for cross-sectional dependence) to quantify the stochastic behavior of time series of Herfindahl–Hirschman index. Our results indicate (i) the energy mix of most of the US states diversified over the period. (ii) Most parts of diversification of energy mix occurred from mid of the 1970s to first half of the 1990s. (iii) Sharp breaks of deterministic part (intercept and slope of the linear trend) of Herfindahl–Hirschman indexes occurred coinciding with oil prices shocks in two decades 1970 and 1980. (iv) The Herfindahl–Hirschman index of most of states display stationary behavior, which indicate the pro-diversification policies, e.g., which are implemented to develop renewable energy sources, have transitory effects and policymakers should implement long-horizon policies to achieve their targeted level of diversification.
This study investigates the role of financial development in moderating the impact of energy diversification on carbon emissions reduction, using a sample of seven major emerging (E7) economies over the period 1995–2018. A panel cointegration test is employed to investigate any long-run equilibrium relationship among variables. The moderating effect is uncovered using a panel autoregressive distributed lag (ARDL) model. The results from the cointegration test reveal the presence of a long-run equilibrium linkage among financial development, energy diversification, and carbon emissions. The panel ARDL model results indicate that the carbo n emissions reduction effect of energy diversification is strengthened by an increased level of financial development in the long-run. Notably, a 1% increase in energy diversification accompanied by a 1% increase in financial development favorably moderates the carbon emissions reduction impact by about 2.11%. This finding is novel and contributes to our understanding of how financial development moderates the carbon emissions reduction effect of energy diversification. Based on this finding, appropriate policy recommendations are suggested to achieve energy transition goals in the E7 economies.
The paper examines the integration between electricity and renewable energy certificate (REC) markets for India. The empirical investigation covers the factors influencing solar and non-solar REC markets, using an autoregressive distributed lag (ARDL) modeling approach. The variables used in this study are the traded volume of solar and non-solar RECs, the traded volume of electricity, wholesale electricity price, and prices of solar and non-solar RECs. The dataset contains monthly time series for the period January 2013–July 2020. The ARDL bounds test results show that the variables are cointegrated. The long-run ARDL estimates indicate that the traded volume of solar REC is influenced by the traded volume of electricity (positive effect), wholesale electricity price (negative effect), the traded volume of non-solar REC (positive effect), and price of solar REC (negative effect). However, the traded volume of non-solar REC is influenced by only traded volume (positive effect) and price (positive effect) of solar REC. Based on the findings of this study, few suggestions are discussed to strengthen the REC market in India.
